Artificial Intelligence and Qualitative Research In Social Work: Do We Need It and If so, How Should We Use It?

The rapid expansion of generative artificial intelligence (AI) has sparked growing interest across academic disciplines, including qualitative research. At the same time, qualitative inquiry in social work remains grounded in interpretation, reflexivity, relational engagement, and ethical accountability. This raises a timely methodological question: Do qualitative researchers need AI, and if they choose to use it, how can they engage these tools without weakening the interpretive and relational foundations of qualitative inquiry? As AI becomes increasingly embedded in academic research, this question has become more urgent (Baez et al., 2026; Paulus & Lester, 2024; van Manen, 2023).

This roundtable brings together qualitative social work scholars who have actively grappled with this question, both through experimentation with AI tools and through deliberate decisions not to use them. Panelists bring expertise across grounded theory, thematic analysis, narrative inquiry, and community-based participatory research. Drawing on firsthand experiences, they will discuss how AI has been used across stages of the research process, including idea development, data organization, early analytic exploration, memo-writing, and writing support, as well as moments of intentional non-use and the reasoning behind those decisions.

Discussion will focus on three intersecting issues. First, the epistemological question: do AI systems, built on pattern recognition and probabilistic inference, align with the commitments of qualitative inquiry, particularly reflexive interpretation, contextual meaning-making, and co-construction of knowledge (Finlay, 2002; Lincoln & Guba, 1985)? Second, the ethical question: how should researchers navigate trust, representation, bias, confidentiality, and data security when AI tools are introduced into research involving human participants, especially those from marginalized communities (Guillemin & Gillam, 2004; Marshall & Naff, 2024)? Third, the disciplinary question: what can qualitative social work scholars uniquely contribute to emerging conversations about responsible AI use in interpretive research, grounded in social work’s commitments to relational accountability, ethics, and social justice (Cleece et al., 2025; Rafieifar, 2026)?

Rather than treating AI as inherently beneficial or inherently harmful, this roundtable centers technological reflexivity as a methodological practice. It asks researchers to examine not only whether AI can be used, but what its use may mean for interpretation, participant relationships, knowledge production, and the ethical commitments of qualitative work (Paulus & Lester, 2024). It also takes seriously concerns from social work that AI-generated outputs may appear coherent while still flattening context, misreading indirect meaning, or reproducing dominant classificatory logics, particularly in research involving marginalized communities (Rafieifar, 2026).

The roundtable will also examine emerging guidance from related disciplines, including education, nursing, and public health, while critically assessing what may or may not translate well to social work contexts. The goal is not to resolve these questions, but to articulate them as a shared methodological agenda for qualitative social work research. In doing so, the session advances the 2027 conference theme by modeling the kind of rigorous, reflexive methodological inquiry needed to strengthen the scientific and ethical foundations of social work research.